Bubble map with Folium in Python

Folium is a Python library based on Leaflet.js JavaScript library. It allows us to create maps in the style of Google Maps with an additional layer of customization.

This post will explain how to use Folium to create bubble maps, a kind of chart where background maps are combined with individual points that represent events or physical objects that have a certain latitude and longitude.

For an introduction to Folium, check this post.
For an introduction to bubble map in Folium, check this post.

Libraries & Data

For creating this chart, we will need to load the following libraries:

matplotlib for plotting the chart
geopandas and geoplot: for spatial data plotting
pandas for loading the data
pypalettes: for the color palette
highlight_text for the annotations

import folium
from folium import plugins
import pandas as pd

Dataset

Let's start by loading shape data:

url = "https://raw.githubusercontent.com/holtzy/The-Python-Graph-Gallery/master/static/data/earthquakes.csv"
df = pd.read_csv(url)
df = df[df['Depth (km)']>=0.01] # depth of at least 10 meters
df.sort_values(by='Depth (km)', ascending=False, inplace=True)
df.head()

	Date	Time (utc)	Region	Magnitude	Depth (km)	Latitude	Longitude	Mode	Map	year
7961	20/02/2019	06:50:47	Banda Sea	5.0	2026	-6.89	129.15	A	-	2019.0
6813	07/07/2019	07:50:53	Eastern New Guinea Reg, P.N.G.	5.4	1010	-5.96	147.90	A	-	2019.0
8293	17/01/2019	14:01:50	Fiji Islands	4.7	689	-18.65	179.44	A	-	2019.0
11258	03/01/2018	06:42:58	Fiji Islands Region	5.5	677	-19.93	-178.89	A	-	2018.0
9530	06/09/2018	18:22:24	Fiji Islands Region	5.8	672	-18.88	179.30	A	-	2018.0

Custom bubble style

The main steps to create a bubble map with folium are:

initiate the map with folium.Map()
iterate over each rows to add each individual point with folium.CircleMarker()

In order to make each point better looking, in the CircleMarker(), we:

change radius to the value in row['Depth (km)']
change the color depending on the magnitude with: color = '#0a9396' if row['Magnitude'] < 4 else '#ee9b00' if row['Magnitude'] < 6 else '#ae2012'
change the opacity with fill_opacity
change border width with weight

# Initialize map
m = folium.Map(
   location=[0, 0], # center around Africa
   zoom_start=2, # dezoom
   tiles='cartodb positron' # background style
)

# Add all the individual earthquakes to the map
for idx, row in df.iterrows():
   color = '#0a9396' if row['Magnitude'] < 4 else '#ee9b00' if row['Magnitude'] < 6 else '#ae2012'
   folium.CircleMarker(
      location=[row['Latitude'], row['Longitude']],
      radius=row['Depth (km)'] * 0.03,
      color=color,
      fill=True,
      fill_color=color,
      fill_opacity=0.5,
      weight=1
   ).add_to(m)

m

Make this Notebook Trusted to load map: File -> Trust Notebook

Tooltip

An interactive map without a tooltip wouldn't be very effective!

Luckily, with the tooltip argument, customizing it is straightforward, and we can even incorporate some HTML into it.

For instance, we can display the Location, Magnitude, Depth, and Date, wrap them in <b> tags for boldness, and set them as level 5 headings (<h5>).

# Initialize map
m = folium.Map(
   location=[0, 0],
   zoom_start=2,
   tiles='cartodb positron'
)

# Add all the individual earthquakes to the map
for idx, row in df.iterrows():
   tooltip_text = f"""
   <h5><b>Location:</b> {row['Region']}</h5>
   <h5><b>Magnitude:</b> {row['Magnitude']}</h5>
   <h5><b>Depth:</b> {row['Depth (km)']} km</h5>
   <h5><b>Date:</b> {row['Date']}</h5>
   """
   color = '#0a9396' if row['Magnitude'] < 4 else '#ee9b00' if row['Magnitude'] < 6 else '#ae2012'
   folium.CircleMarker(
      location=[row['Latitude'], row['Longitude']],
      radius=row['Depth (km)'] * 0.05,
      color=color,
      fill=True,
      fill_color=color,
      fill_opacity=0.5,
      weight=1,
      tooltip=folium.Tooltip(tooltip_text, sticky=True)
   ).add_to(m)
   
m

Make this Notebook Trusted to load map: File -> Trust Notebook

Automatically cluster points

folium comes with a set of plugins to add new features super easily!

For example here we use the MarkerCluster() plugin to automatically cluster the marker into groups when zooming-out.

And in order for this to work: we add the markers to the map with .add_to(marker_cluster) instead of .add_to(m)

from folium import plugins

# Initialize map
m = folium.Map(
   location=[0, 0],
   zoom_start=2,
   tiles='cartodb positron'
)

# Add earthquake data with clustering
marker_cluster = plugins.MarkerCluster().add_to(m)

# Add all the individual earthquakes to the map
for idx, row in df.iterrows():
   tooltip_text = f"""
   <h5><b>Location:</b> {row['Region']}</h5>
   <h5><b>Magnitude:</b> {row['Magnitude']}</h5>
   <h5><b>Depth:</b> {row['Depth (km)']} km</h5>
   <h5><b>Date:</b> {row['Date']}</h5>
   """
   color = '#0a9396' if row['Magnitude'] < 4 else '#ee9b00' if row['Magnitude'] < 6 else '#ae2012'
   folium.CircleMarker(
      location=[row['Latitude'], row['Longitude']],
      radius=row['Depth (km)'] * 0.05,
      color=color,
      fill=True,
      fill_color=color,
      fill_opacity=0.7,
      weight=0.4,
      tooltip=folium.Tooltip(tooltip_text, sticky=True)
   ).add_to(marker_cluster)

m

Make this Notebook Trusted to load map: File -> Trust Notebook

Going further

Contact & Edit

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